Accelerating consensus on coevolving networks: The effect of committed individuals

P. Singh, S. Sreenivasan, B. K. Szymanski, and G. Korniss
Phys. Rev. E 85, 046104 – Published 6 April 2012

Abstract

Social networks are not static but, rather, constantly evolve in time. One of the elements thought to drive the evolution of social network structure is homophily—the need for individuals to connect with others who are similar to them. In this paper, we study how the spread of a new opinion, idea, or behavior on such a homophily-driven social network is affected by the changing network structure. In particular, using simulations, we study a variant of the Axelrod model on a network with a homophily-driven rewiring rule imposed. First, we find that the presence of rewiring within the network, in general, impedes the reaching of consensus in opinion, as the time to reach consensus diverges exponentially with network size N. We then investigate whether the introduction of committed individuals who are rigid in their opinion on a particular issue can speed up the convergence to consensus on that issue. We demonstrate that as committed agents are added, beyond a critical value of the committed fraction, the consensus time growth becomes logarithmic in network size N. Furthermore, we show that slight changes in the interaction rule can produce strikingly different results in the scaling behavior of consensus time, Tc. However, the benefit gained by introducing committed agents is qualitatively preserved across all the interaction rules we consider.

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  • Received 23 September 2011

DOI:https://doi.org/10.1103/PhysRevE.85.046104

©2012 American Physical Society

Authors & Affiliations

P. Singh1,2, S. Sreenivasan1,2,3,*, B. K. Szymanski2,3, and G. Korniss1,2

  • 1Department of Physics, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, New York 12180, USA
  • 2Social and Cognitive Networks Academic Research Center, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, New York 12180-3590, USA
  • 3Department of Computer Science, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, New York 12180, USA

  • *sreens@rpi.edu

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Issue

Vol. 85, Iss. 4 — April 2012

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